Immune checkpoint inhibitors (ICIs) are extending the survival of patients with advanced, metastatic cancer, across many cancer types. Remarkably, immunotherapies may be curative, yet, only a fraction of cancer pa- tients have strong durable responses to ICIs. Response rates also differ greatly between cancer types, and some ICIs are only effective against a handful of cancers. The reasons for this remain unclear, underscoring the need for further research. Many ICIs, like antibodies targeting the PD-1/PD-L1 pathway, act on tumor-specific T cells that are already fighting the cancer at the time the patient is diagnosed with disease. The therapies reinvigorate T cells and cause them to attack and sometimes destroy the cancer. Little is known about the T cells that mediate thera- peutic responses or the factors that modulate their therapeutic efficacy. Thus, there is great interest in deter- mining how these therapies work and in augmenting them so that response rates increase. Unfortunately, it has not been easy, because few animal models recapitulate the natural biology of human cancer and elicit de- tectable anti-tumor immune responses. Genetically engineered mouse (GEM) models are widely used for stud- ies in cancer biology because they allow investigators to study developing tumors and to understand how tu- mors change over the course of disease. Yet, these gold-standard models are not used for cancer immunology studies because tumors do not express neoantigens, which are required for anti-tumor T cell responses. It has been challenging to develop GEM models where tumors express neoantigens. To remedy this problem, we engineered the ?NINJA? mouse, and, in this proposal, we will use NINJA to generate ?immunogenic? GEM models for cancer (i.e., models that elicit anti-cancer immune responses). We will standardize immunogenic models for lung and pancreatic cancer, investigate how neoantigens alter the immune cell infiltrates into tu- mors, and confirm their translational potential as faithful mimics of human cancer. Moreover, we will develop cell line and organoid models from these immunogenic GEMs, which will greatly increase the available tools for researchers in lung and pancreatic cancer. These state-of-the-art models will allow scientists to look at lung and pancreatic tumors at early stages (before cancers would be diagnosed in a patient), and to figure out how these early tumors and immune cells interact. Moreover, our studies will validate NINJA as a platform that can be used by other investigators for the genera- tion of immunogenic GEMs for other cancer types. As these models can be used to improve responses of pa- tients to immunotherapy, NINJA will be useful for enhancing the applicability of almost any GEM model for translational research.